Earth Monitoring from A New Generation of Geostationary Satellites
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 93137
Special Issue Editors
Interests: radiative transfer theory; vegetation monitoring; climate, ecosystem modeling
Interests: machine learning/AI; radiative transfer; big data analytics; biomass monitoring
Interests: climate analysis; land surface monitoring; geostationary sensors
Special Issues, Collections and Topics in MDPI journals
Interests: ecosystem modeling; vegetation-climate interactions; remote sensing of vegetation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Earth monitoring, particularly from polar orbiting (LEO) satellites, has improved dramatically over the past four decades. Advances in sensor technologies coupled with sophisticated algorithms now allow routine retrievals of important bio-geophysical/chemical variables used in long-term climate monitoring as well as operational resources management. Geostationary (GEO) satellites, of which the role has been limited to atmospheric dynamics and weather in the past, are now poised to make significant contributions to land monitoring.
The era of the advanced geostationary satellites was ushered in by the launch of Japanese Himawari-8 on 7 October, 2014, followed by Himawari-9 (Japan), GOES-16 (US) and FY-4 (China), respectively, in late 2016, and GOES-18 (US) in early 2018. The next few years will also see the deployment of advanced GEO satellites by Korean and European meteorology/space agencies. The assembly is underway constructing a GEO-ring of advanced sensors with a global coverage outside the polar regions.
All of the new generation GEO satellites carry advanced imagers with typical specifications of 16 spectral bands, spatial resolutions from 0.5km to 2km depending on bands, and variable image cadence from 30 seconds to 15 minutes with routine full disk scans every 10 to 15 minutes. In many ways, these advanced geostationary imagers provide land and atmosphere monitoring capabilities comparable to flagship LEO sensors like MODIS and VIIRS while offering far greater temporal resolution and the complementary view-illumination geometries. These characteristics of the GEO sensors make them particularly suited to fill gaps in LEO coverage due to cloudiness, enable more accurate measurement of surface energy balance and water fluxes, as well as to monitor rapid changes in the land surface (e.g., snow, flood, fires, diurnal variations in LST, etc.), ocean (e.g., algal blooms and sediment plumes), and transient properties of the atmosphere (e.g., aerosols, smoke, and dust events).
Further enhancements in observation capability can emerge from applications that exploit the complementary features of the advanced GEO and the LEO sensors and the synergistic use of data from both types of satellites. Such possibilities include, for example, merging the finer spatial resolution of the LEO sensors with the higher temporal resolution of the GEO sensors, exploiting complementary information from simultaneous observations with different view-illumination geometries, and the fusion of GEO and LEO products to global coverages and/or long-term time periods. Opportunities also exist in leveraging information between GEO, LEO and other types of sensors (e.g., hyperspectral sensors and radar/LiDAR) to maximize the quality of the potential data products.
This Special Issue welcomes manuscripts that illustrate the developments and applications of data products from the new generation GEO sensors and their potential synergistic use with LEO and other types of sensors for advanced monitoring of Earth’s land processes. Examples of such topics include (but are not limited to):
- Calibration of the new generation GEO sensors in terms of geometrical, spectral, and radiometric accuracies;
- Cloud detection, aerosol retrieval and atmospheric correction;
- Assessment of the view-illumination geometries of GEO sensors and their impacts on the measurements;
- GEO Land surface product development and validation strategy;
- Near-real time monitoring of fires, floods, and other rapid land surface changes;
- Ecological and environmental applications of GEO data products;
- Data fusion with GEO, LEO, and other types of satellite data sources;
- Applications of machine learning and AI technologies in GEO data processing and analytics;
- Technology advances (e.g., cloud optimized workflows, HPC systems, container technologies) in GEO product generation and distribution;
Dr. Weile Wang
Dr. Sangram Ganguly
Dr. Satya Kalluri
Dr. Ramakrishna Nemani
Guest Editors
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Keywords
- geostationary satellites
- wildfires
- evapotranspiration
- primary production
- albedo
- machine learning
- cloud computing
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